Celebrating the Dead Sea Scrolls : a Canadian collection
Bibliographic record
Abstract
This volume celebrates the discovery of Dead Sea their contents, the community that wrote and preserved them, and new scientific issues that arise from Scrolls studies. The essays, in four sections, explore the origins and text of scripture, the interpretation of scripture in Second Temple Judaism, the identity and practices of the movement associated with Qumran and the Scrolls, and the extensive contributions of Canadian projects and scholarship. Eight color plates are included in the volume. The contributors are Eileen Schuller, Jason Kalmon and Jaqueline S. du Toit, Jean Duhaime, Andrew B. Perrin, Benjamin H. Parker, Peter W. Flint and Kyung S. Baek, Eugene Ulrich, Manuel Jinbachian, Martin G. Abegg Jr., Emanuel Tov, Steve Mason, Daniel K. Falk, Wayne McCready, Ian W. Scott, Chad Martin Stauber, Ted M. Erho, Robert David with the collaboration of Eric Bellavance, Francis Daoust, Marie-France Dion, Dorothy M. Peters, Hindy Najman, C. J. Patrick Davis, Lorenzo DiTommaso, Cecilia Wassen, and Craig A. Evans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".